class_docstr: The DDRNet implementation based on PaddlePaddle.
  
  The original article refers to
  Yuanduo Hong, Huihui Pan, Weichao Sun, et al. "Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes"
  (https://arxiv.org/abs/2101.06085)
  
  Args:
      num_classes (int): The unique number of target classes.
      in_channels (int, optional): Number of input channels. Default: 3.
      block_layers (list, tuple): The numbers of layers in different blocks. Default: [2, 2, 2, 2].
      planes (int): Base channels in network. Default: 64.
      spp_planes (int): Branch channels for DAPPM. Default: 128.
      head_planes (int): Mid channels of segmentation head. Default: 128.
      enable_auxiliary_loss (bool): Whether use auxiliary head for stage3. Default: False.
      pretrained (str, optional): The path or url of pretrained model. Default: None.
code: def _make_layers(self, block, inplanes, planes, blocks, stride=1):
      downsample = None
      if stride != 1 or inplanes != planes * block.expansion:
          downsample = nn.Sequential(
              nn.Conv2D(
                  inplanes,
                  planes * block.expansion,
                  kernel_size=1,
                  stride=stride,
                  bias_attr=False,
              ),
              nn.BatchNorm2D(planes * block.expansion),
          )
      layers = []
      layers.append(block(inplanes, planes, stride, downsample))
      inplanes = planes * block.expansion
      for i in range(1, blocks):
          if i == (blocks - 1):
              layers.append(
                  block(inplanes, planes, stride=1, no_relu=True)
              )
          else:
              layers.append(
                  block(inplanes, planes, stride=1, no_relu=False)
              )
      return nn.Sequential(*layers)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 3 for calling the DualResNet obj's underlying member method code with example usage: obj._make_layers(block, inplanes, planes, blocks, stride) and returns: nn